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We report the demonstration of the first axial AlInN ultraviolet core-shell nanowire light-emitting diodes with highly stable emission in the ultraviolet wavelength range. During epitaxial growth of the AlInN layer, an AlInN shell is spontaneously formed, resulting in reduced nonradiative recombination on the nanowire surface. The AlInN nanowires exhibit a high internal quantum efficiency of ~52% at room temperature for emission at 295 nm. The peak emission wavelength can be varied from 290 nm to 355 nm by changing the growth conditions. Moreover, significantly strong transverse magnetic (TM) polarized emission is recorded, which is ~4 times stronger than the transverse electric (TE) polarized light at 295 nm. This study provides an alternative approach for the fabrication of new types of high-performance ultraviolet light emitters.

Electron leakage is one of the critical challenges in AlGaN ultraviolet (UV) light-emitting diodes (LEDs). In this regard, a p-type AlGaN electron-blocking layer (EBL) has been utilized to suppress electron leakage. However, it affects the hole injection due to the generation of positive polarization sheet charges at the hetero-interface of the EBL and the last quantum barrier (QB). To address this problem, we propose an EBL-free AlGaN UV LED using polarization-engineered graded QBs instead of conventional QBs. The proposed structure could enhance the carrier confinement in the active region and significantly reduces electron leakage due to the progressively increased effective conduction band barrier heights. Substantially, the proposed structure exhibits higher optical power and wall-plug efficiency at 60 mA current injection, which are boosted by ~85.9% and ~53.6% compared to the conventional structure. Such a unique LED design could pave the way for the next generation of high-power deep UV light sources.

The Chu Lai granite is widespread throughout the northern Kontum massif and is an important key in understanding the evolution of the Kontum region and its vicinity. The study presents new data on geochemistry, zircon U-Pb ages, and Nd-Hf isotopes from the Chu Lai granite which allows to constrain the Paleozoic tectonic evolution of the Kontum massif. The Chu Lai granite contains alumina-rich minerals (garnet and muscovite), is depleted in Ba, Nb, Ta, Sr and Ti but enriched in Rb, Th, U and Pb. These geochemical characteristics indicate a S-type nature of the Chu Lai granite. The zircon ɛHf values vary between −16.7 to −1 and Hf model ages (TDM2) between 1.50 and 2.49 Ga as well as whole rock ɛNd values of −8.3 to −5.8 and Nd model ages (TDM2) between 1.67 and 1.89 Ga. The Hf-Nd isotope data indicate that the Chu Lai granite was derived from partial melting of Paleoproterozoic metasedimentary material. The LA-ICP-MS zircon U-Pb ages range from 445 Ma to 454 Ma, suggesting a crystallization of the Chu Lai granite during the Ordovician-Silurian period.

Introduction: Cancer is a highly lethal disease with a significantly high mortality rate. One of the most commonly used methods for treatment is radiation therapy. However, cancer treatment using radiotherapy is a time-consuming process that requires significant manual work from planners and doctors. In radiation therapy treatment planning, determining the dose distribution for each of the regions of the patient’s body is one of the most difficult and important tasks. Nowadays, artificial intelligence has shown promising results in improving the quality of disease treatment, particularly in cancer radiation therapy. Objectives: The main objective of this study is to build a high-performance deep learning model for predicting radiation therapy doses for cancer and to develop software to easily manipulate and use this model. Materials and Methods: In this paper, we propose a custom 3D convolutional neural network model with a U-Net-based architecture to automatically predict radiation doses during cancer radiation therapy from CT images. To ensure that the predicted doses do not have negative values, which are not valid for radiation doses, a rectified linear unit (ReLU) function is applied to the output to convert negative values to zero. Additionally, a proposed loss function based on a dose–volume histogram is used to train the model, ensuring that the predicted dose concentrations are highly meaningful in terms of radiation therapy. The model is developed using the OpenKBP challenge dataset, which consists of 200, 100, and 40 head and neck cancer patients for training, testing, and validation, respectively. Before the training phase, preprocessing and augmentation techniques, such as standardization, translation, and flipping, are applied to the training set. During the training phase, a cosine annealing scheduler is applied to update the learning rate. Results and Conclusions: Our model achieved strong performance, with a good DVH score (1.444 Gy) on the test dataset, compared to previous studies and state-of-the-art models. In addition, we developed software to display the dose maps predicted by the proposed model for each 2D slice in order to facilitate usage and observation. These results may help doctors in treating cancer with radiation therapy in terms of both time and effectiveness.

This study presents a novel approach to mitigate electron overflow in deep ultraviolet (UV) AlGaN light-emitting diodes (LEDs) by integrating engineered quantum barriers (QBs) with a concave shape and an optimized AlGaN superlattice (SL) electron blocking layer (EBL). The concave QBs reduce electron leakage by lowering the electron thermal velocity and mean free path, enhancing electron capture in the active region. The SL EBL further reduces electron overflow without compromising hole transport. At a wavelength of ~253.7 nm, the proposed LED demonstrates a 2.67× improvement in internal quantum efficiency (IQE) and a 2.64× increase in output power at 150 mA injection, with electron leakage reduced by ~4 orders of magnitude compared to conventional LEDs. The efficiency droop is found to be just 2.32%.

In the present work, nickel–zinc oxide (Ni-ZnO) particles have been fabricated through a modified polyol route at 250°C. The highly porous Ni-ZnO samples developed were of high crystalline quality and exhibited great potential for dye-sensitized solar cell (DSSC) applications on account of the quadrupled intensity values of short-circuit current density of around 1.42 mA/cm2, in contrast to 0.31 mA/cm2 for a bare zinc oxide (ZnO) device. The conversion efficiency of the Ni-ZnO DSSC was measured to be 0.416% which is ∼ 6 times higher than that a of ZnO solar cell. Detailed characterization techniques including x-ray diffraction, photoluminescence, scanning electron microscopy and energy-dispersive x-ray spectroscopy were performed on the samples. The Ni-ZnO samples were found to be crystalline with a hexagonal wurtzite lattice structure. The improved efficiency of Ni-ZnO stems from the enhanced absorption and large surface area of the composite.

Introduction: Evidence on post–COVID-19 conditions is emerging. This study aims to assess post-COVID conditions and related factors in COVID-19 patients in Central Vietnam. Methodology: A descriptive cross-sectional study was performed on people who have recovered from COVID-19 at least 2 weeks prior to the online survey. Participants were interviewed face-to-face after 6 and 9 months from the first survey. Results: 53 patients (21.2%) were confirmed to have persistent symptoms, of which, 100% and 94.3% reported prolonged fatigue and full-body weakness respectively. Loss of appetite was reported by 90.6%, while persistent cough, insomnia, and trouble sleeping were reported by 86.3% of patients. Headaches and dyspnea were reported by 69.5% and 56.8% respectively, while other symptoms had lower rates. The prevalence of post-COVID condition showed a statistically significant relationship with the time of infection, duration of illness, treatment place, use of herbal medicine, adherence to the 5K message from Vietnam's Ministry of Health, and daily saltwater mouthwash (p < 0.05). However, the use of medicine and supplements was not related to the post-COVID condition (p > 0.05). After 6 months, 125 participants were interviewed face-to-face, and only 15 people (12.0%) reported having post-COVID symptoms, mainly prolonged fatigue (33.3%) and persistent cough (26.7%). After 9 months, these 15 patients no longer had symptoms related to the post- COVID-19 condition. Conclusions: The post-COVID condition can persist for several weeks or months, but will mostly be in remission after 6 months, and completely resolve after 9 months from the onset of the infection.

Basalt-related pyrope from Southeast Vietnam occurs as both xenocrysts and xenoliths, and is collected from secondary deposits. The garnet is transparent deep orange to light red when observed with transmitted light. The gemmological characteristics, as well as Raman and FTIR spectra, confirm it is pyrope. The chemical composition yields molar percentages of [Py.sub.72.0-75.3][Al.sub.14.8-18.3] [Gr.sub.9.2-9.9] (where Py = pyrope, Al = almandine and Gr = Grossular) and an average chemical formula of [([Mg.sub.2.15][Fe.sup.2+.sub.0.42][Ca.sub.0.27][Mn.sub.0.01]).sub.2.85][Al.sub.2.14]([Si.sub.2.99][O.sub.12]). The surfaces of the pyrope exhibit resorption that occurred during transport to the surface in basaltic magma. Examination of coronae (kelyphitic texture) surrounding the xenolithic garnets with a petrographic microscope, combined with FTIR spectroscopy, shows that the pyrope originated from a deep garnet peridotite source.

We have developed a novel substrate-transfer procedure for phosphor-free nanowire (NW) white light-emitting diodes (LEDs), wherein the NWs are grown directly on an SiO 2 etch-stop layer. By applying this technique, InGaN/GaN NW LEDs were successfully transferred from SiO 2 /Si(100) substrates to copper substrates to reduce substrate absorption and improve heat dissipation. Compared with NW LEDs on Si, NW LEDs on copper substrates have several advantages, including enhanced output power and better current–voltage characteristics. We also show that white light emission by NW LEDs on copper substrates is highly stable.

Nanoelectronic Devices and Applications presents reviews on recent advances in nanoelectronic device design and new directions for their practical use. The volume includes 16 edited chapters that cover novel material systems, band engineering, modelling and simulations, fabrication and characterization techniques, and their emerging applications. The discussions presented in this book are based on current understandings on innovations and future trends, and references are provided for advanced scholars. Chapter 1 presents an overview of recent innovations and future prospects in III-nitride semiconductor technologies for RF, power, digital and quantum applications. Chapter 2 reports new trends in GaN-based optical devices for sensing and micro-display applications. Chapter 3 shows current interests in nanophosphors and their utilizations in improving device performance of InGaN nanowire light-emitting diodes (LEDs). Recent studies on the effect of potential profile on the carrier transport in AlGaAs based double quantum well structures and their applications are presented in Chapter 4. The recent progress in high-electron-mobility transistors (HEMTs) is presented through Chapters 5, 6, and 7. A comprehensive review on ?-Ga2O3 emphasizing material properties, growth approaches, and its applications for next-generation high-power nanoelectronics; the effect of dielectric layers on the characteristics of AlN/?-Ga2O3 HEMTs are presented in Chapter 8 and 9 respectively. Chapters 10-14 summarize the recent studies in field-effect transistors (FETs) adopting different materials and structures. Chapter 15 presents current research in 2D Tungsten Diselenide (WSe2) with special focus on the material properties, device structures, applications, and challenges. Finally, Chapter 16 presents a systematic review of memristors, and memristive semiconductor devices. The book is intended as a primary resource for elective subjects in advanced electronics and computer engineering courses at university level. Researchers and industry professionals will also learn about emerging trends and state-of-the-art research in nanoelectronics. Readership Students in advanced engineering courses; researchers and industry professionals.